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707,693 tools. Updated 2026-10-27 05:49

"Matomo" matching MCP tools:

  • Provisions a managed MySQL (or MariaDB) database on a dedicated VM on your private network - the relational-database resource (use this instead of create_database when the app needs MySQL/MariaDB, e.g. WordPress, NextCloud, Matomo, many PHP/LAMP apps). Requires a recent plan_managed_datastore. For app deployments, prefer deploy_app database:'managed' with db_engine mysql/mariadb so plan_deploy includes and wires the DB automatically. It is PRIVATE - reachable only from another instance on the same private network, via the DB's internal/private IP (port 3306), not a public address. Get the ids from plan_managed_datastore/list_flavors/list_private_networks/list_keypairs. Provisioning takes ~5 min; poll list_relational_databases until status='ready', then the connection details (private_ip, port 3306, db_name, db_user) are populated. MySQL is created with mysql_native_password auth so older clients/apps connect cleanly. (ClickHouse is a separate resource - use create_clickhouse / list_clickhouse_databases.)
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  • Deploys an app to a VM and exposes it at a public https://<name>-<id>.redu.cloud URL. The container is built ON the VM. PREREQS - run check_deploy_prerequisites first for network_id + keypair_name, then plan_deploy for cost approval. Source can be git repo or prepare_upload source_token. PORT must be the real app listen port. DATASTORES ARE MANAGED BY DEFAULT: each one you reported in send_signals runs as a managed store started at your signal and is wired with no settings (DATABASE_URL and PG*/MYSQL_*, REDIS_URL, QDRANT_URL with QDRANT_API_KEY); without a signal, pass database:'managed' (db_engine 'postgres', or 'mysql'/'mariadb' for WordPress/Matomo/LAMP), redis:'managed' or qdrant:'managed'. For WordPress/WooCommerce cluster intent, do not use generic stateless deploy: pass app_profile, cluster_target:true, database:'managed', db_engine:'mariadb' or 'mysql', cluster_media_mode:'media_space', and either media_space_id or create_media_space:true. Redu mounts the media space into wp-content/uploads and refuses unsafe local uploads. Build+provision takes minutes; poll list_deployments/get_deployment. ROUTE: when plan_deploy returned recommended_route:'compose', do NOT use this tool for that folder: deploy its recommended_compose_file with deploy_compose (compose_file, recommended_service as service, recommended_port as port), for the reason in route_reason. The exceptions are route_next's: this tool builds the folder's Dockerfile instead only if the user asked for a build from source, the user changed the code the Dockerfile builds (check git status and unpushed commits in the folder), or the image cannot be pulled.
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  • Turns YOUR repo classification (you scan the repo and pass what you found) into a complete, approvable deploy plan WITHOUT creating anything. ⚡ REDU NEEDS THREE FILES IF THEY EXIST - redu.md, the compose file, the Dockerfile - and there are two ways to give them. ⭐ BEST, for an upload-mode deploy: run prepare_upload FIRST and pass its `source_token`; redu reads all three straight out of the upload you already made, the upload stays deployable, and you emit nothing. Pasting the same files costs you 20-29 KB of output for bytes the server already has. Otherwise (git mode) paste `redu_md` (cat redu.md), `compose_yaml`, `dockerfile`. Either way you do NOT read or interpret them; redu parses them SERVER-SIDE and returns (a) a short digest, (b) `pin_dname` so a redeploy keeps the SAME public URL, and (c) `preflight` - preemptive fixes for known failure patterns found in YOUR repo, each learned from a real failed build. Giving redu these files is the single highest-value thing you can do for a first deploy. picks the VM + managed-Postgres sizes, prices them at the real pricing_rules rates, and checks they FIT your quota - so a plan that can't provision is caught HERE, before any spend. You pass what you detected in the repo (runtime, port, needs_postgres/redis/clickhouse/vector_db); it returns resources + £/hr + £/mo + a feasibility verdict + a checkpoint summary to confirm with the user. Defaults: app VM m1.medium, managed Postgres m1.small, managed ClickHouse m1.medium; pass single_vm to collapse the app + Postgres onto one VM. SET needs_clickhouse:true FOR ANY ANALYTICS-SHAPED APP (Plausible, PostHog, Langfuse, Matomo, SigNoz, or anything with a clickhouse image / CLICKHOUSE_* env / a ClickHouse client dep): those products keep config in Postgres and EVERY EVENT in ClickHouse, so the events tier is a second VM with a second line on the bill: measured 2026-08-07, omitting it quoted GBP 53.29/mo for a GBP 65.99/mo deployment. It is sized, quota-checked and priced here; unlike Postgres and Redis it is not auto-wired by deploy_app, so the plan tells you to run plan_managed_datastore engine:'clickhouse' -> create_clickhouse and pass CLICKHOUSE_* env yourself. A Qdrant vector DB is managed like the other datastores (vector_engines in send_signals; qdrant:'managed' without a signal); pgvector lives in the managed Postgres. In a session with send_signals the platform sizes every machine by measurement, so heavy_build, memory_heavy and needs_compose change no size there. Any containerizable app works (node, python, go, ...) - it deploys as a container, so the language doesn't gate it. Set serves_http:false for a non-web repo (a library, CLI, or language runtime with no HTTP server) and it returns a clean not-a-web-service verdict instead of a costed VM plan. Set heavy_build:true for resource-heavy builds (compiled-from-source native code, a monorepo/turborepo build, a large Node heap) and it raises the app VM to a build-capable floor so the on-VM build doesn't get OOM-killed. Set memory_heavy:true for a RAM-forward app whose persistent state lives in a MANAGED DB / external store (Next.js like cal.com/cal.diy, Rails, Django, JVM/Java apps) - it sizes onto a memory-optimized SMALL-DISK flavor (m1.mem16/m1.mem32: full RAM, a lean 40 GB disk instead of 160 GB) that costs less and snapshots/clusters far faster; do NOT set it if the app keeps lots of data on local disk. Also returns a brand-named markdown report (Mermaid diagram + cost) to SHOW the user only in guided mode; write no file from it. Every deploy leaves TWO MANDATORY files at the repo root with DIFFERENT purposes, both written ONCE at the end from the deployment that actually ran (get_deployment), after you verified it works: redu-deploy-plan.md = what this run deployed, and redu.md = the DURABLE deploy memory the NEXT deploy reads. If a redu.md exists, READ it FIRST and reuse its known-good plan + recorded fixes; if NONE exists, one MUST be created at the end of the deploy (get_deployment returns redu_md_bootstrap_markdown for exactly that case; when a redu.md DOES exist, pass it as redu_md and write the merged redu_md_markdown). They are SEPARATE files - even if your own memory/notes from a prior deploy call redu-deploy-plan.md 'the record', the durable record is redu.md, so do not skip creating it. ROUTE: from a source_token (pass port too: it tells the platform which compose service is the app) the plan can also carry recommended_route:'compose', the platform's route for that folder, with every recommended_* and route_* field it sent (recommended_compose_file, recommended_service, recommended_port, recommended_image, route_reason, route_next): then deploy that compose file with deploy_compose (compose_file), with recommended_service as service and recommended_port as port (the HOST port the app service publishes, not the port the app listens on inside its container), not deploy_app, unless route_next's conditions for building the Dockerfile with deploy_app hold.
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  • Analityka ruchu sklepu z Matomo (tylko agregaty). Wizyty, akcje, unikalni AI, platformy i zamówienia. Bez argumentów raportuje wczoraj w Europe/Warsaw. period last_1/last_7/last_30 zamiast dat; compare=previous_period porównuje z poprzednim oknem. data_status rozróżnia zero od braku danych; unikalnych z wielu dni nie sumuj. Nazwę platformy podawaj tylko z by_provider; unknown = nieznana. Podaj źródło i niepewności z metadata.attribution_caveats. AI referrals to natywny kanał Matomo; kampanie AI są osobno, boty i cytowania nie są mierzone.
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  • A
    license
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    quality
    C
    maintenance
    Enables read-only analytics queries through the Matomo Reporting API, with project-local credential configuration and tools for sites, reports, visits, goals, segments, dimensions, and bounded report batches.
    MIT

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